Search Results (389)

Odour recognition with low-cost gas sensors is challenging in open-air settings due to the non-specificity of the sensors and environmental variability. This can be mitigated by incorporating additional information into the classification process. This paper investigates odour-image multimodality in two case-studies of increasing complexity: banana ripening in open-air environment and strawberry ripening in a glasshouse environment. Data were collected using custom acquisition platforms equipped with cameras and MOX gas sensors operated with temperature modulation. For the visual modality, image classification (MobileNetV3) and object detection (YoloV5) models are trained. For the odour modality, established classical machine learning methods (Random Forest, XGBoost, SVM and Logistic Regression) and neural networks (1D-CNN, LSTM, MLP, and ELM) are employed. Each modality is analysed independently and together to critically assess scenarios in which combining modalities provides a clear advantage over using either modality alone. Results show that models trained on odour data achieve high accuracy in controlled environments but underperform in more dynamic open-air settings. Image-based models are sensitive to the image quality in all environments; however, they are more robust when deployed in different environments. Lastly, it is demonstrated that decision fusion consistently increases the accuracy, by as much as +12.36% in the banana ripening and +3.63% in the strawberry ripening scenario. Where decision fusion does not improve classification accuracy significantly, it is shown that the multimodal approach can still be leveraged to identify high-confidence predictions by selecting samples where both modalities agree on the label. Full article

The traditional solid-state method was employed in this study to prepare Mn-Zn ferrite. By adjusting the sintering temperature and the MoO₃ doping ratio, the evolution of its structural and magnetic properties was systematically investigated. Fe₂O₃, MnO, and ZnO were used as the main raw materials, with MoO₃ serving as an additive. MoO₃ was doped at molar ratios ranging from 0 to 1000 ppm under experimental conditions involving a sintering temperature between 1125 °C and 1165 °C and an oxygen concentration of 1.5%. The addition of an appropriate amount of MoO₃ led to an increase in the Q value, which consequently resulted in a reduction in the loss. The formation of a single-phase spinel structure was confirmed by X-ray diffraction analysis. Observations of the surface morphology revealed that the grain size also increased with the increase in MoO₃ content, a trend consistent with the enhanced grain growth kinetics at higher MoO₃ levels. In this study, a Mn-Zn ferrite material with excellent comprehensive performance was successfully prepared under the optimal conditions of a sintering temperature of 1150 °C and a MoO₃ doping concentration of 500 ppm. A Q value of 22.3 was obtained for this material at 25 °C, while a Q value of 15.7 was obtained at 100 °C. At room temperature, a Q value of 192.4 was measured at a test frequency of 500 kHz, and a Q value of 137.2 was measured at 1 MHz. At a frequency of 500 kHz, a loss of 27.1 kW/m³ was observed at 25 °C, and a loss of 53.6 kW/m³ was observed at 100 °C. At a frequency of 1 MHz, a loss of 88.2 kW/m³ was recorded at 25 °C, while a loss of 183.7 kW/m³ was recorded at 100 °C. Additionally, the lattice constant was stabilized in the range of 8.52–8.53 Å, indicating favorable structural stability. Full article

Emission control of diesel particulate matter (soot) combustion is important for environmental reasons. Catalysts are indispensable for optimizing these processes, as they significantly reduce the combustion temperature. In this work, mixed oxides (cerium–copper, cerium–manganese, and cerium–molybdenum) were prepared by co-precipitation under reasonably similar synthesis conditions, and the effects of their chemical composition on diesel soot combustion were evaluated using the Printex U model particulate. Thermogravimetric analysis (TG/DTG) and temperature-programmed oxidation coupled with mass spectrometry (TPO/MS) were employed for activity characterization. Structural analyses revealed the presence of nanocrystalline phases containing CeO₂ (fluorite), CuO (monoclinic), Mn₂O₃ (cubic), and MoO₃ (orthorhombic), depending on the catalyst composition. The most effective catalysts exhibited an equimolar oxide composition (CeO₂–MO_x). Tests performed at optimized calcination temperatures and with the addition of promoters led to the identification of optimal combustion conditions. The highest activity, corresponding to the lowest combustion temperature, was observed in the following order: CeO₂–Mn₂O₃ > CeO₂–CuO > CeO₂–MoO₃, with values of 382, 409, and 425 °C, respectively, under tight-contact conditions at a Printex U:catalyst ratio of 1:20. With the addition of a 10% Ag₂O promoter, the CeO₂–Mn₂O₃ catalyst further reduced the oxidation temperature to 376 °C. Reusability tests generally indicated a 10–20% decrease in catalytic activity by the third reaction cycle. Full article

Developing active and robust catalysts for the acidic oxygen evolution reaction (OER) with reduced Ir loading is still a challenge in the industrial production of green H₂. In this work, several catalysts ranging from single metal oxides (e.g., IrO₂) to high-entropy oxides (IrNiMnFeCoCuVO_x) were synthesised through thermal decomposition in air to study the effect of the mixed-oxide composition in terms of activity and stability towards the acidic OER. Catalysts were named MOx-n, with n being the number of metal elements in the mixture. The results show that the activity of rutile IrO₂ can be improved by introducing other elements into the composition. The best performance was obtained for MOx-4 to MOx-5, which delivered a current density of 10 mA cm⁻² at an overpotential (η₁₀) of 279 ± 4 mV; approx. 100 mV lower than IrO₂ at a comparable Ir loading and with better stability. Nevertheless, further increasing the complexity of the mixed oxide resulted in an evident degradation in terms of activity and stability. It is worth noting that surface dissolution and reconstruction occurred with all mixed-oxide catalysts, including high-entropy configurations. Full article

This study reports the synthesis, spectroscopic characterization, and biological evaluation of a novel moxifloxacin hydrazide derivative (MOX-H) and its metal complexes with Co(II), Ni(II), Cu(II), VO(IV), and Gd(III). The ligand was synthesized by hydrazinolysis of moxifloxacin hydrochloride, and the resulting hydrazide was subsequently complexed with the respective metal salts. The interaction between MOX-H and the metal ions yielded the corresponding complexes, formulated as [Co(H₂O)Cl(MOX-H)₂]Cl·2.5H₂O, [Ni(H₂O)Cl(MOX-H)₂]Cl.4.5H₂O, [VO(MOX-H)₂]SO₄.3.5H₂O, [Gd (H₂O)(MOX-H)₂(NO₃)₂]NO₃.2H₂O, and [Cu(MOX-H)₂(H₂O)Cl]Cl·xH₂O (where x = 2, 2.5, 0.5, for products synthesized via template, microwave-assisted, and hydrothermal methods, respectively). The synthesized analogues were characterized by elemental analysis (CHN), FT-IR, UV-visible, and ¹H NMR spectroscopy, and mass spectrometry, as well as thermogravimetric (TG/DTG) and magnetic measurements. FT-IR spectra confirmed coordination through the hydrazide carbonyl and amine groups, while UV–visible and magnetic data indicated predominantly octahedral geometries. The thermal behavior exhibited multistep decomposition with activation parameters supporting exothermic processes. When compared to the free ligand, the metal complexes showed increased antimicrobial activity against both Gram-positive and Gram-negative bacteria and fungus species, particularly for the Co(II) and Cu(II) complexes, which showed the largest inhibition zones. The Cu(II)–MOX-H complex exhibited the lowest MIC values (4.88–9.76 µg/mL) among all tested compounds, confirming its outstanding antibacterial potency and high sensitivity compared to the free ligand and standard drug. Cytotoxicity assays demonstrated selective anticancer activity, with the Cu(II)–MOX-H complex showing the highest potency (IC₅₀ ≈ 2.95 µM against MCF-7 and IC₅₀ ≈ 0.98 µM against HepG-2), while maintaining minimal toxicity toward normal cells. These findings were corroborated by molecular docking investigations, which showed that the MOX-H complexes had substantial binding affinities (−9 to −10 kcal/mol) toward DNA topoisomerase II, consistent with their observed biological effects. Full article

Efficient hydrogen separation and purification technology plays a crucial role in the hydrogen energy industry. VB-group alloy membranes have demonstrated favorable hydrogen permeability, but their hydrogen embrittlement resistance remains generally insufficient. This work designed Nb₃₅Hf₃₀Co₁₅Ni_20-xMo_x high-entropy alloy (HEA) membranes with regulated Ni and Mo contents. The influences of HEA compositions on microstructures, hydrogen permeability and hydrogen embrittlement resistance were systematically analyzed. On the one hand, the doping of Mo increased the volume and proportion of BCC-Nb phase, thus promoting hydrogen permeation; on the other hand, the hydrogen solubility was reduced, thus enhancing the hydrogen embrittlement resistance. The lattice distortion effect, sluggish diffusion effect and optimized Mo content collectively enhanced the comprehensive performance of Nb₃₅Hf₃₀Co₁₅Ni_12.5Mo_7.5, achieving a hydrogen permeability (Φ) of 2.68 × 10⁻⁸ mol H₂ m⁻¹·s⁻¹·Pa^−0.5 at 673 K and exhibiting excellent hydrogen embrittlement resistance, showing no hydrogen-induced fractures even at room temperature. This quantitatively demonstrates its excellent performance, which represents a certain breakthrough compared to related studies. The novel Nb₃₅Hf₃₀Co₁₅Ni_20-xMo_x HEA membranes offer excellent hydrogen permeability and improved hydrogen embrittlement resistance, thereby highlighting the potential for future hydrogen purification applications. Full article

The increasing diffusion of plant-based milk alternatives poses new challenges at the intersection of food safety and consumer experience, particularly regarding allergen cross-contamination and beverage performance during preparation. Traditional quality control strategies are typically confined to upstream production stages and are unable to address individualized risks and sensory variability at the point of consumption. In this study, we propose an embedded volatilomic sensing approach that combines metal oxide semiconductor (MOX) sensor arrays with lightweight artificial intelligence algorithms to enable real-time, on-device decision-making. The volatilome of four commercially available plant-based milk beverages (oat, almond, soy, and coconut) was characterized using GC–MS/SPME as a reference method, while a MOX-based electronic nose provided rapid, non-destructive sensing of volatile fingerprints. Linear Discriminant Analysis demonstrated clear discrimination among beverage types based on their volatile signatures, supporting the use of MOX sensor arrays as functional descriptors of compositional identity and process-related variability. Beyond beverage classification, the proposed framework is designed to support future implementation of (i) screening for anomalous volatilomic patterns potentially compatible with accidental cow’s milk carryover in shared preparation settings and (ii) adaptive tuning of preparation parameters (e.g., foaming-related settings) in smart beverage systems. The results highlight the role of embedded volatilomic intelligence as a unifying layer between personalized risk-aware screening and sensory-oriented process control, paving the way for intelligent food-processing appliances capable of autonomous, real-time adaptation at the point of consumption. Full article

In recent years, two-dimensional (2D) materials have attracted growing attention for their application in chemoresistive gas sensors. Among these materials, graphene stands out due to its exceptional electrical, mechanical, and chemical properties. A simple and low-cost method for producing graphene involves the use of a laser to induce its formation on carbon-rich substrates, such as polyimides. This technique, first introduced in 2014, has been successfully applied in the fabrication of various types of sensors, including pressure sensors, temperature sensors, biosensors, and gas sensors. For chemoresistive gas sensors, laser-induced graphene (LIG) has been used either as an electrode or as part of the nanocomposite forming the active sensing layer. Moreover, this technology has allowed the use of heating elements. Sensing performance, including sensitivity and selectivity, can be tailored by incorporating different materials into the nanocomposite, such as metallic nanoparticles, metal oxides, or conductive polymers. These modifications can be implemented using low-cost and scalable fabrication methods, making this approach highly suitable for the development of affordable and efficient gas sensors. In this contribution, we present a comprehensive overview of the contributions, reported from the proposal of LIG technology in 2014 to 2025, about the use of this fabrication process in the development of chemoresistive gas sensors. Full article

Background: Wastewater treatment plants (WWTPs) are hotspots of antimicrobial resistance (AMR) due to inputs from diverse anthropogenic sources. Aeromonas spp., ubiquitous in aquatic environments, often carry clinically relevant antibiotic resistance genes (ARGs) and can persist beyond fecal contamination indicators, making them promising sentinel organisms for AMR dissemination. The aim of this study was to assess the suitability of Aeromonas spp. in this role by characterizing resistance profiles, associated virulence factor genes (VFGs), genetic mobility, and persistence across wastewater and drinking water treatment processes in the Barcelona metropolitan area, Spain. Methods: Isolates were phenotypically characterized and screened for ARGs, VFGs, integrons, and heavy metal tolerance genes, followed by whole-genome sequencing (WGS). Biofilm formation was assessed in vitro. Conjugation assays with Escherichia coli evaluated horizontal gene transfer (HGT) potential. Results: A total of 428 antibiotic-resistant Aeromonas spp., the most abundant antibiotic-resistant bacteria isolated during the 2023 sampling campaigns from two WWTPs and one drinking water treatment plant (DWTP), were characterized. Trimethoprim/sulfamethoxazole (SXT) non-susceptibility was most frequent (72%), followed by cefoxitin resistance (65.4%). The sul1 (57.5%) and bla_MOX (78.6%) genes predominated among SXT- and β-lactam-resistant isolates. The merA gene was detected in 23.6%; 97.9% harbored at least one VFG (aerA, act, fla, alt, or hlyA), and 70.3% carried intI1. Half formed biofilm. Conjugation confirmed bi-directional HGT, and WGS revealed persistent ST3458 clones across treatment stages. Conclusions: WWTPs and DWTPs act as reservoirs of antibiotic-resistant Aeromonas spp., demonstrating persistence and HGT potential. Findings support their use as sentinel organisms for AMR surveillance in aquatic environments and for assessing treatment efficacy, highlighting variability across treatment types and locations, and reinforcing their relevance for urban water reclamation monitoring. Full article

Background/Objective: This study addresses a significant knowledge gap in the literature concerning antibiotic resistance genes (ARGs) in arid soils by employing metagenomic approaches to characterise their diversity, using Kuwait as a model environment. Methods: Soil samples were collected from two agriculturally managed sites (K1 and K3) and one coastal unmanaged site (K2), representing distinct ecological conditions. Results: Taxonomic profiling revealed notable variation in microbial communities at both the phylum and genus levels. Alpha diversity analyses based on the Chao1 and Shannon indices indicated that agricultural soils exhibited greater microbial richness and diversity than the coastal soil. Beta diversity analysis further demonstrated substantial differences in microbial community composition among the sites. Consistent with previous soil microbiome studies, ARGs such as tetA, aac(3)-Ib, sul1, qep, muxB, mexW, mexB, and macB were detected across the sites. However, the identification of distinct clinically relevant resistance genes, including ugd, blaOXA-18, blaCMY-19, blaMOX-7, blaFOX-7, blaLRA-12, and novA, suggests the influence of site-specific or extreme selective pressures. Conclusions: Several of the detected ARGs appear to be rare or previously unreported in soil environments. Although the sample size is too small to support broad generalisations, the detection of ugd in soil is particularly noteworthy, suggesting that soils may serve as reservoirs of polymyxin resistance, potentially undermining the effectiveness of polymyxin antibiotics. Full article

Efficient and low-cost electrocatalysts play a crucial role in hydrogen production through the electrolysis of water. Molybdenum (Mo) carbide with a similar electronic structure to Pt was selected, and both α-MoC_1−x and α-MoC_1−x/β-Mo₂C electrocatalysts were successfully fabricated for electrochemical hydrogen evolution. A continuous optimization of the hydrothermal and carbonization conditions was carried out for the preparation of α-MoC_1−x. The biphasic molybdenum carbide catalysts were further achieved via vanadium doping with a phase transition of molybdenum carbide from α to β, which increased the specific surface area of the electrocatalyst. It was found that the V-Mo_xC catalyst obtained at a Mo/V molar addition ratio of 100:5 exhibited the best hydrogen production performance, with a β to α phase ratio of 0.827. The overpotential of V-Mo_xC at η₁₀ decreased to 99 mV, and the Tafel slope reached 65.1 mV dec⁻¹, indicating a significant improvement in performance compared to the undoped samples. Excellent stability was obtained for the as-prepared electrocatalyst for water splitting over 100 h at a current density of 10 mA cm⁻². Full article

High-temperature self-lubricating materials with stable tribological performance across a wide temperature range are essential for advanced mechanical systems under extreme conditions. However, balancing mechanical strength and lubrication efficiency remains a key challenge. This study fabricated CoCrFeNiMox-Ni/MoS₂-Ag-Cr₂O₃ composites (x = 0.2, 0.5, 1) via spark plasma sintering, aiming to investigate the effect of Mo content on their microstructure, mechanical properties, and tribological behavior. Microstructural analysis showed that the as-sintered composites mainly consist of FCC phase, Cr₂O₃, Ag, and Ni/MoS₂. Increasing Mo content from 0.2 to 1 wt.% significantly promoted the formation of hard σ-phase intermetallics, leading to increased hardness (up to 546 HV) and yield strength (peaking at 502 MPa). Tribological tests at 25–800 °C indicated continuous lubrication behavior in all composites. The minimum friction coefficient was 0.23, and wear rates remained below 10⁻⁶ mm³/N·m. In the low-to-medium temperature range, lubrication was dominated by the synergistic effect of Ni/MoS₂ and Ag: Ni/MoS₂ formed low-shear-strength films, while Ag reduced surface adhesion. Meanwhile, the Mo solid solution strengthened and the σ-phase enhanced wear resistance by improving hardness and inhibiting plastic deformation. At high temperatures, tribochemical reactions generated lubricating films composed of oxides and molybdates, which maintained tribological performance by reducing direct contact between friction pairs. This study demonstrates that Mo-doped high-entropy alloy composites can serve as high-performance wide-temperature self-lubricating materials, providing a basis for designing “matrix-lubricant” systems for extreme-temperature applications. Full article

Background/Objectives: The prediction of survival after resection of colorectal liver metastases is crucial for planning treatment strategies. Several prognostic scores have been proposed, but their reliability is debated. The present study aims to review available prognostic scores, focusing on their performance and the methodological approaches adopted for their evaluation. Methods: A systematic literature review was conducted using PubMed, Embase, and the Cochrane Database, including studies published between January 2015 and June 2024. Only English-language studies reporting the external validation of prognostic models were included. A random-effects meta-analysis was performed. Results: Overall, 48 prognostic scores were externally validated across 48 studies (n = 33,602 patients). A total of 286 performance measurements were reported, utilizing 17 different metrics and considering four outcomes: overall survival (OS), cancer-specific survival, recurrence-free survival (RFS), and recurrence rate. For OS, the pooled C-index values for the Fong, GAME, and RAS mutation Clinical Risk scores were 0.578 (0.570–0.587), 0.609 (0.592–0.625), and 0.579 (0.471–0.688), respectively. For RFS, the pooled C-index for the Fong score was 0.616 (0.578–0.653). Scores incorporating genetic, immunological and radiomic data performed better than purely clinical ones (C-index = 0.610, 0.657 and 0.635, respectively, vs. 0.585, p < 0.05). Analogously, the scores including perioperative data outperformed preoperative ones (C-index = 0.671 vs. 0.600, p = 0.007). Conclusions: The current survival prediction relies on scores with low reliability (C-index ≤ 0.65). Despite the abundance of available data, their heterogeneity and variable quality have limited their usability. Future research should prioritize the development of new prognostic tools and the standardization of prognostic modeling and reporting. Full article

Background/Objectives: Keratitis is an ocular disease caused by microbial infection or by non-infectious damage due to UV light exposure, chemical exposure, or eye injuries. Methods: Moxifloxacin-loaded ufasomes (MOX-UFAs) were optimized using a full factorial design (1².2³) after being prepared by the vortex mixing method. The study evaluated the effects of the oleic acid amount, surface active agent (SAA) amount, and SAA type as independent factors on the entrapment efficiency percent (EE%), particle size (PS), polydispersity index (PDI), zeta potential (ZP), and the amount released after 6 h (Q6h%). Results: The optimized ufasomes (UFAs) formulation was spherical, with an EE% of 78.37 ± 3.91%, PS of 203.13 ± 20.31 nm, PDI of 0.334 ± 0.016, and ZP of −25.42 ± 1.27 mV. The in vitro release of moxifloxacin (MOX) from the UFAs was maintained for more than 6 h in the range of 40.0–75.0%. The optimum MOX-UFAs formulation was incorporated into an in situ gel (Pluronic F-127/HPMC K4M). The ex vivo studies (corneal permeation and confocal laser scanning microscopy) proved the successful retention of the MOX-UFAs-laden in situ gel. Furthermore, the in vitro and in vivo antimicrobial studies revealed their significant antimicrobial effect against Pseudomonas aeruginosa. In addition, the Draize test proved the tolerability of MOX-UFAs-laden in situ gel in animals. Conclusions: The incorporation of MOX-UFAs into Pluronic F-127/HPMC K4M in situ gel could successfully provide sustained ocular delivery and improve the bioavailability of MOX for the management of keratitis. Full article

KANECS is a 3D multigroup neutronics code based on the Simplified Spherical Harmonics (SP_N) approximation and the Continuous Galerkin Finite Element Method (CGFEM). In this work, the code is extended to solve the time-dependent neutron kinetics by implementing a fully implicit backward Euler scheme for the neutron transport equation and an implicit exponential integration for delayed neutron precursors. These schemes ensure unconditional stability and minimize temporal discretization errors, making the method suitable for fast transients. The new formulation transforms each time step into a transient fixed-source problem, which is solved efficiently using the GMRES solver with ILU preconditioning. The kinetics module is validated against established benchmark problems, including TWIGL, the C5G2 MOX benchmark, and both 2D and 3D mini-core rod-ejection transients. KANECS shows close agreement with the reference solutions from well-known neutron transport codes, with consistent accuracy in normalized power evolution, spatial power distributions, and steady-state eigenvalues. The results confirm that KANECS provides a reliable and accurate framework for solving neutron kinetics problems. Full article